a. Using the pairs of values for all 10 points, find the equation of the regression line. b. After removing the point with coordinates (8,3), use the pairs of values for the remaining 9 points and find the equation of the regression line. c. Compare the results from parts (a) and (b). a. What is the equation of the regression line for all 10 points? y=x (Round to three decimal places as needed.) b. What is the equation of the regression line for the set of 9 points? (Round to three decimal places as needed.) c. Choose the correct description of the results below. OA. The removal of the point has a significant impact on the regression line. OB. There is no regression line for the second case because the data are in a pattern. OC. The regression line is very similar in both cases. OD. The regression line changes, but the change is small. Q Q

MATLAB: An Introduction with Applications
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### Regression Line Analysis

#### a. Equation of the Regression Line for All 10 Points

Using the pairs of values for all 10 points, find the equation of the regression line. 
\[ \hat{y} =  \_ +  \_  x \] 
(Round to three decimal places as needed.)

#### b. Equation of the Regression Line for the Set of 9 Points

After removing the point with coordinates (8,3), use the pairs of values for the remaining 9 points and find the equation of the regression line.
\[ \hat{y} =  \_  +  \_  x \] 
(Round to three decimal places as needed.)

#### c. Comparison of Results

Choose the correct description of the results below:
- A. The removal of the point has a significant impact on the regression line.
- B. There is no regression line for the second case because the data are in a pattern.
- C. The regression line is very similar in both cases.
- D. The regression line changes, but the change is small.

#### Graph Explanation

To the right of the text, there is a scatter plot graph showing the distribution of data points. The graph has an x-axis labeled from 0 to 10 and a y-axis labeled from 0 to 10. There are 10 blue dots representing the pairs of values, with one point specifically at coordinates (8,3). This point will be removed for part (b) of the analysis to observe its impact on the regression line. The rest of the points are distributed in such a way that students can visualize changes in the regression line when this point is removed.

This analysis helps in understanding how outliers or specific data points can influence the calculations and the resulting regression line in statistical data.
Transcribed Image Text:### Regression Line Analysis #### a. Equation of the Regression Line for All 10 Points Using the pairs of values for all 10 points, find the equation of the regression line. \[ \hat{y} = \_ + \_ x \] (Round to three decimal places as needed.) #### b. Equation of the Regression Line for the Set of 9 Points After removing the point with coordinates (8,3), use the pairs of values for the remaining 9 points and find the equation of the regression line. \[ \hat{y} = \_ + \_ x \] (Round to three decimal places as needed.) #### c. Comparison of Results Choose the correct description of the results below: - A. The removal of the point has a significant impact on the regression line. - B. There is no regression line for the second case because the data are in a pattern. - C. The regression line is very similar in both cases. - D. The regression line changes, but the change is small. #### Graph Explanation To the right of the text, there is a scatter plot graph showing the distribution of data points. The graph has an x-axis labeled from 0 to 10 and a y-axis labeled from 0 to 10. There are 10 blue dots representing the pairs of values, with one point specifically at coordinates (8,3). This point will be removed for part (b) of the analysis to observe its impact on the regression line. The rest of the points are distributed in such a way that students can visualize changes in the regression line when this point is removed. This analysis helps in understanding how outliers or specific data points can influence the calculations and the resulting regression line in statistical data.
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